from intro import info

terms = ['Chris', 'Brown', 'And', 'Rihana']
from nltk.corpus import wordnet
from nltk.probability import FreqDist, ConditionalFreqDist
fd = FreqDist()
cfd = ConditionalFreqDist()

print dir(wordnet)

for each in terms:
    wordnet.findtheinfo(each)
"""
for text in wordnet.files():
  for sent in wordnet.tagged_sents(text):
    for (token, tag) in sent:
      fd.inc(tag)
      cfd[token].inc(tag)

fd['NN']
152470
for each in terms:
    for pos in cfd[each]:
        print each, pos, cfd[each][pos]
        """
